Depth estimation using defocused stereo image pairs

Abstract

In this paper we propose a new method for estimating depth using a fusion of defocus and stereo, that relaxes the assumption of a pinhole model of the camera. It avoids the correspondence problem of stereo. The main advantage of this algorithm is simultaneous recovery of depth and image restoration. The depth (blur or disparity) in the scene and the intensity process in the focused image are individually modeled as Markov random fields (MRF). It avoids the windowing of data and allows incorporation of multiple observations in the estimation procedure. The accuracy of depth estimation and the quality of the restored image are improved compared to the depth from defocus method, and a dense depth map is estimated without correspondence and interpolation as in the case of stereo.